From ML to AI in Biopharma R&D
Date:
The transition from machine learning (ML) to artificial intelligence (AI) in biopharma R&D marks a pivotal shift in how data-driven methods are applied to scientific discovery. This talk explores the evolution from predictive ML models to more autonomous, agentic AI systems capable of reasoning, planning, and interacting within complex biomedical environments. We will examine how these systems are being used to accelerate drug discovery, optimise clinical trial design, and uncover novel biological insights—while also addressing the challenges of interpretability, reproducibility, and regulatory alignment. Special attention will be given to the role of agentic AI in orchestrating workflows, generating hypotheses, and adapting to new data in real time. By drawing on recent academic and industry collaborations, the session will highlight opportunities for interdisciplinary research and the implications for the future of computational biomedicine.